BPG is committed to discovery and dissemination of knowledge
Prospective Study Open Access
Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Gastrointest Pharmacol Ther. Jun 5, 2026; 17(2): 114876
Published online Jun 5, 2026. doi: 10.4292/wjgpt.v17.i2.114876
Effect of cholecystectomy on liver fat and fibrosis in metabolic dysfunction-associated steatotic liver disease patients
Khellaf Amalou, Rym Rekab, Sabrina Fadel, Abderezak Bousloub, Department of Gastroenterology, Mohamed Seghir Nekkache, Algiers 16000, Algeria
Nassila Belal, Department of Radiology, Mohamed Seghir Nekkache, Algiers 16000, Algeria
Abdelghani Tibouk, Department of Pathology, Mohamed Seghir Nekkache, Algiers 16000, Algeria
Yasmine Ghedada, Department of Biology, Mohamed Seghir Nekkache, Algiers 16000, Algeria
Nabil Debzi, Department of Gastroenterology, CHU Mustafa, Algiers 16000, Algeria
ORCID number: Khellaf Amalou (0000-0003-2626-0815).
Author contributions: Amalou K is the main contributor to the manuscript and the first author; Amalou K contributed to making significant, original, and insightful intellectual contributions; participated in the conception or planning of the research; obtaining manuscript data by conducting experiments; performing literature reviews, or carrying out surveys or interviews; analyzing the findings of the manuscript through statistical analysis and preparing figures and/or tables; planning and writing the manuscript; and participating in responding to reviewers’ comments and manuscript revision after manuscript submission; Belal N, Tibouk A, Ghedada Y, Rekab R, Fadel S, Debzi N, Bousloub A are first and foremost responsible for the finalization of the content of the parts that they completed or participated in. In particular, the other authors contributed to verifying the content of the parts involving them in each iteration of the revised manuscript, verifying their name and initials, verifying their affiliations; and verifying the PDF full text, figures, tables, and references in the manuscript. All authors have read and approved the final manuscript.
Institutional review board statement: The study protocol has been reviewed and approved by Hôpital Mohamed Seghir Nekkache.
Clinical trial registration statement: This study is registered in the Pan African Clinical Trials Registry, with the registration number: PACTR202511511917109.
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
CONSORT 2010 statement: The authors have read the CONSORT 2010 Statement, and the manuscript was prepared and revised according to the CONSORT 2010 Statement.
Data sharing statement: Data are available from the corresponding author.
Corresponding author: Khellaf Amalou, PhD, Assistant Professor, Department of Gastroenterology, Mohamed Seghir Nekkache, Kouba 246, Algiers 16000, Algeria. amalou_kh@yahoo.fr
Received: October 1, 2025
Revised: December 2, 2025
Accepted: February 3, 2026
Published online: June 5, 2026
Processing time: 238 Days and 8.2 Hours

Abstract
BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is highly prevalent worldwide. Experimental studies have shown that cholecystectomy (Chx) increases metabolic dysfunction-associated steatotic liver (MASL) and is associated with MASLD in large retrospective cohort studies.

AIM

To prospectively evaluate the effect of Chx on MASL and fibrosis, assess the prevalence of MASLD, and identify its risk factors in this population.

METHODS

There were 213 MASLD patients enrolled, with 103 being Chx and 110 being non-Chx patients. The patients were followed up for 36 months.

RESULTS

Body mass index increased in the Chx group (30.15 ± 4.08 to 31.58 ± 4.64) vs (31.90 ± 4.07 to 30.03 ± 4.16) in the control group (P < 0.001). Median controlled attenuation parameter increased from 300.77 ± 47.42 to 314.17 ± 44.7 (Chx) and decreased from 325.06 ± 41.74 to 296.36 ± 56.51 (control) (P < 0.01). MASL/magnetic resonance imaging (MRI) moved from 14.22 ± 8.64 and 18.55 ± 8.57 at baseline to 15.98 ± 7.93 and 13.88 ± 8.12 at the end of the study (P < 0.001). The biological scores of MASL (fatty liver index, hepatic steatosis index, and lipid accumulation product) all progressed in the Chx group and regressed in the control group (P < 0.001). The prevalence of hepatic steatosis was 42.38% (Chx). Risk factors associated with significant hepatic steatosis were metabolic syndrome, Chx, MASL/MRI, and fatty liver index scores. Risk factors associated with advanced fibrosis are body mass index, aspartate aminotransferase/alanine aminotransferase ratio, diabetes mellitus score, stiffness, and Chx. Stiffness, obesity, Chx, gamma-glutamyl transferase, and MASL/MRI are associated with metabolic dysfunction-associated steatohepatitis (MASH) lesions.

CONCLUSION

Chx increases MASL and fibrosis. MASLD prevalence in the Chx group is higher than in the overall population.

Key Words: Metabolic dysfunction-associated steatotic liver disease; Cholecystectomy; Hepatic fibrosis; Metabolic dysfunction-associated steatotic liver; Metabolic dysfunction-associated steatohepatitis

Core Tip: Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as the most common chronic liver disease. It is significantly linked to diabetes, obesity, and other cardiometabolic risk factors. It is more pronounced in cholecystectomized patients than in those with lithiasis. Recent research suggests that the gallbladder may help to maintain overall metabolic homeostasis. Recent data suggests that cholecystectomy (Chx) has metabolic effects and may operate as a risk factor for MASLD and metabolic syndrome. In our study, we found that Chx enhances metabolic dysfunction-associated steatotic liver and fibrosis. MASLD prevalence is higher in the Chx group than in the general population.



INTRODUCTION

Metabolic dysfunction-associated steatotic liver disease (MASLD) is currently the most common chronic liver disease, and its prevalence is predicted to rise further[1-4]. MASLD is closely associated with diabetes, obesity, and other cardiometabolic risk factors[5]. Obesity is more prevalent among young people in many African countries than malnutrition[6]. MASLD is frequently associated with obesity, diabetes, atherosclerosis, and cholesterol gallstones. It is more obvious in cholecystectomized individuals than in those with lithiasis, but it is also common among biliary lithiasis patients. Algeria has been undergoing an epidemiological transformation for three decades, with significant changes in food habits and levels of physical activity in urban areas. The overall prevalence of being overweight is 56.8% (48.2% in males and 62.8% in women), with obesity at 21.2%[7-9]. MASLD is usually associated with cholesterol gallstones. This behavior is common in people with biliary lithiasis, although it is more noticeable in patients who have undergone a cholecystectomy (Chx) than in those who have lithiasis[9,10]. Chx is the most common treatment for gallbladder disease[11,12]. This surgical treatment is commonly performed all over the world and has been connected to moderate long-term consequences[13-16]. Given the high concentration of fibroblast growth factor 19 (FGF19) in the gallbladder mucosa, new studies suggests that the gallbladder regulates bile acid metabolism, which helps to maintain overall metabolic balance[17-19]. Recent retrospective studies have demonstrated that Chx has metabolic consequences and may be a risk factor for MASLD and metabolic syndrome (MS)[20,21]. Murine model studies reveal that Chx increases metabolic rates, serum triglyceride levels, hepatic triglyceride concentrations, and cholesterol-low density lipoprotein production. Furthermore, Chx has been associated with poor postprandial glucose control and patient weight gain[22-24]. The goal of this study is to evaluate the effects of Chx on hepatic steatosis and fibrosis in MASLD patients, investigate its prevalence in people who have had a Chx, and identify associated risk factors.

MATERIALS AND METHODS
Patient selection

This single-center study compares two patient groups: One group received Chx for symptomatic gallbladder stones (GBS), while the other had a non-lithiasic gallbladder as a control. Both had histological lesions consistent with the diagnosis of MASLD. Anthropometric, biochemical evaluations [alanine aminotransferase (ALT), homeostasis model assessment (HOMA) test, fibrosis scores including aspartate aminotransferase to platelet ratio index (APRI), fibrosis 4, non-alcoholic fatty liver disease fibrosis score (NFS), and body mass index (BMI), aspartate aminotransferase/ALT ratio, diabetes mellitus (BARD) scores], and morphological assessments [FibroScan® Echosens, France, acoustic radiation force fibrosis (ARFI), and magnetic resonance imaging (MRI)] have been employed to monitor the evolution of MASLD, which was first identified through histological examination. This study included patients aged 18 to 75 who underwent Chx for symptomatic GBS and showed MASLD in intraoperative liver biopsy (LB), as well as people with liver stiffness of 7.2 kPa or higher who were scheduled for percutaneous LB 24 hours to 48 hours after FibroScan®. We excluded pregnant women, patients with ascites, those who have declined LB surgery, those with diabetes complications, excessive alcohol consumers (more than 30 g per day for men and 20 g per day for women), patients with hepatitis (viral B/C, autoimmune, or cholestatic), patients with specimens measuring less than 10 mm and fewer than 6 portal areas, patients with advanced cardiovascular disease, malignant neoplasia, and those taking steatogenic medication. Individuals with MASLD were diagnosed using established criteria[25-29], which included a clinical examination, hepatic ultrasonography, and histological evidence of metabolic dysfunction-associated steatotic liver (MASL), metabolic dysfunction-associated steatohepatitis (MASH), or cirrhosis.

Clinical and biochemical evaluations: The initial clinical assessment consisted of recording a medical history, completing a physical examination, and measuring height and weight to calculate BMI. Venous blood samples were conducted after a 12-hour fast. The central laboratory at Mohamed Seghir Nekkache Hospital tested serum glucose, lipids, insulin, ALT, and aspartate aminotransferase levels. The HOMA index was used to assess insulin resistance during fasting. The fibrosis scores (APRI, fibrosis 4, NFS, BARD) and hepatic scores [fatty liver index (FLI), lipid accumulation product (LAP), hepatic steatosis index (HSI)] were assessed.

Histopathological examination

All patients underwent a FibroScan® 48 hours before their LB. We perform liver biopsies on non-Chx patients with hepatic stiffness greater than 7.2 kPa and all Chx candidates[26]. A biological evaluation and imaging (ARFI, liver MRI) were performed on the same day as the LB, or within one week. The date of diagnosis or study entry matched the date of LB in the control group and two weeks after Chx in the cholecystectomized group. A pathologist who specialized in liver pathology analyzed the various samples histologically. The lesions were classified using the steatosis, activity and fibrosis score, non-alcoholic fatty liver disease activity score, and Metavir criteria, respectively.

Imaging analysis

All patients underwent a comprehensive evaluation of non-invasive indicators in accordance with established recommendations[25,30-32]. Fibrosis in FibroScan® is classified as F0-F1, F2, F3, and F4 based on stiffness measurements of < 7.2, 7.2-8.6, 8.7-10.2, and > 10.3 kPa[26]. Hepatic steatosis is classified as S0, S1, S2, and S3 according to controlled attenuation parameter (CAP) values of < 237, 238-259, 260-292, and > 292 dB/m, respectively[31]. Siemens ARFI is classified as F0-F1, F2, F3, and F4 based on velocity values < 1.16, 1.16-1.48, 1.48-1.63, and > 1.64[32]. All hepatic MRIs were performed using Siemens 3 Tesla MRI equipment (Magnetom Vida 3T, Siemens Healthineers, China). MASL was classified into four groups: S0, S1, S2, and S3, based on measurement limits of less than 8.9%, 8.9%-16.3%, 16.3%-25%, and more than 25%[33].

Dietary limitations

All patients were asked to adhere to dietary restrictions for at least 36 months, with an emphasis on reducing calorie intake, particularly from carbohydrates and fats, while favoring proteins, fresh vegetables, and plant-based foods. We urge that you engage in physical activity, particularly walking for 45 minutes every two weeks. A nutritional examination was not performed. Data were collected at the time of diagnosis, six, twelve, twenty-four, and thirty-six months thereafter.

Statistical analysis

Parametric data were presented as mean ± SE, whereas non-parametric data were presented as medians with interquartile ranges. The t-test was used to compare parametric data. Non-parametric data were analyzed using the Wilcoxon test, and frequencies were compared using paired χ2 tests. Logistic regression was used for both multivariate and univariate studies.

RESULTS
Patient characteristics

From March 1, 2021 to September 30, 2022, 218 persons were identified during the initial screening, with 5 being excluded due to vesicular neoplasia, colonic adenocarcinoma, and prostate cancer. We followed 213 people diagnosed with MASLD for at least 36 months (Figure 1). The average age of patients at diagnosis was 51.66 years (± 11.97), with a range of 29 years to 74 years. The sex ratio was 0.99, with 107 men (50.2%) and 106 women (49.8%). Patients came from various regions of Algeria (Table 1). Among the patients, 165 (77.5%) resided in cities, 48 (22.5%) in rural areas, and 36 (16.9%) were unemployed. Table 2 displays the computed biological scores combined with histological and morphological data.

Figure 1
Figure 1 Patent recruitment and follow-up flowchart. NAFLD: Non-alcoholic fatty liver disease; MASLD: Metabolic dysfunction-associated steatotic liver disease; Chx: Cholecystectomy; MRI: Magnetic resonance imaging; ECG: Electrocardiography; HOMA-IR: Homeostasis model assessment index.
Table 1 Patient’s clinico-biological database, n (%)/median (interquartile range).

Total (n = 213)
Chx+ (n = 103)
Chx- (n = 110)
P value
Sex male107 (50.2)31 (30.1)76 (69.1)< 0.001
Age (years)51.66 ± 11.9752.16 ± 10.9751.51 ± 9.970.237
High blood pressure102 (49.9)54 (52.4)48 (44)0.139
Diabetes mellitus104 (48.8)41 (39.8)63 (57.3)0.008
Hypercholesterolemia18 (8.5)9 (8.7)9 (8.2)0.53
Hypertriglyceridemia27 (12.7)10 (9.7)17 (15.5)0.146
Metabolic syndrome152 (71.4)65 (63.1)87 (79.1)0.007
Weight (kg)89.17 (54-136)84.16 (54-123)93.87 (56-136)< 0.001
Size (cm)169.28(150-190)166.99 (154-190)171.42 (150-188)< 0.001
BMI (kg/m2)31.06 (18.2-43.8)30.16 (18.2-41.7)31.9 (24.3-43.8)0.002
Hip circumference (cm)109.73 (78-140)109.98 (78-140)109.50 (80-136)0.12
Waist size (cm)108.65 (78-138)107.62 (78-131)109.62 (83- 138)0.10
Chest perimeter (cm)107.50 (80-128)107.6 (80-126)107.4 (80-128)0.23
AST (UI/L)29.95 (10.30-165.00)29.47 (10.9-165)30.40 (10.3- 89.0)0.68
ALT (UI/L)34.14 (7.0-161.0)29.96 (7-161)38.05 (9-117.65)0.009
GGT (UI/L)45.25 (8.9-299.3)43.03 (8.9-299.3)47.33 (12.46-211)0.41
PAL (UI/L)77.63 (21.13-370)79.37(12-370)76.00 (28.80-167)0.44
prothrombin rate (%)98.87 (80-100)99.03(80-100)98.71 (80-100)0.53
Platelets (G mmol/L)229.89 (89-502)230.32(113-502)229.50(89-470)0.92
LDL Cholesterol (mmol/L)2.95(0.67-5.89)3.10(0.80-5.89)2.81 (0.67-5.40)0.02
HDL Cholesterol (mmol/L)1.08 (0.21-4.10)1.1(0.60-4.10)1.07 (0.21-4.1)0.72
Triglyceride (mmol/L)1.82(0.58 15.24)1.86(0.58-15.24)1.79 (0.62-7.6)0.70
HBA1c (%)6.45 (4.2-10.35)6.19(4.23-9.20)6.69 (4.4-10.35)0.001
Albumin (G/L)44.42 (31.93-54.80)44.42(33.02-54)44.42(31.9-54.8)0.99
Table 2 Biological and histological data, n (%)/median (interquartile range)/mean ± SE.
Scores M0
Total (n = 213), mean (extreme)
Chx+ (n = 103), mean (extreme)
Chx- (n = 110), mean (extreme)
P value
BARD score2.74 (0-4)2.76 ± 1.042.72 (0-4)0.79
HOMA test7.879 (1.0-18.7)7.37 ± 2.528.32 (2-18.7)0.023
FLI score78.52 (7-100)75.71 ± 17.6281.15 (31-100)0.016
LAP score82.73 (15.-372.40)82.5 ± 40.0982.94 (20.1-372.4)0.94
HSI score42.88 (25.2-79.4)40.62 ± 5.7644.99 (29.1-79.4)< 0.001
APRI score0.33 (0.1-2.8)0.34 ± 0.320.33 (0.1-0.7)0.67
FIB 4 score2.64 (0.25-283.00)4.16 ± 2.771.22 (0.25-3.73)0.26
NFS score-1.13 (-6.57 to 3.36)-1.10 ± 1.44-1.16 (-6.57 to 3.36)0.78
Length LB (mm)22.27 (10-45)23.10 (10-45)22.89 (10-45)0.16
Portal area (n)15.99 (6-28)15.19 (6-28)16.74 (7-28)0.036
Steatosis (%)29.53 (5-70)23.79 (5-70)34.90 (5-70)< 0.001
NAS score4.51 (1-8)3.93 (1-8)5.05 (2-8)< 0.001
SAF score6.36 (2-11)5.56 (2-11)7.11 (3-11)< 0.001
Steatosis grade: S05 (2.3)5 (4.9)0< 0.001
S1114 (53.5)68 (66)46 (41.8)< 0.001
S281 (38.0)28 (27.2)53 (48.2)< 0.001
S313 (6.1)2 (1.9)11 (10)< 0.001
Steatosis type: Absent4 (1.94 (3.9)0 (0)0.007
Pure macrolobular18 (8.5)12 (11.7)6 (5.5)0.004
Pure microlobular7 (3.3)6 (5.8)1 (0.9)0.21
Mixed184 (86.4)81 (78.6)103 (93.6)0.003
Ballooning: Absent23 (10.8)15 (14.6)8 (7.3)0.001
Present (size = hepatocyte)57 (26.8)37 (35.9)20 (18.2)0.001
Present (size = hepatocyte 2n)133 (62.4)51 (49.5)82 (74.5)0.001
Apoptotic bodies: Absent or rare162 (76.1)89 (86.4)73 (66.4)0.001
Present51 (23.9)14 (13.6)37 (33.6)0.001
Mallory’s body: Absent160 (75.1)88 (85.4)72 (65.5)0.003
Present52 (24.4)15 (14.6)37 (33.6)0.003
Lobular inflammation: 0 foyer21 (9.9)14 (13.6)7 (6.5)< 0.001
1à 2 foyers93 (43.7)58 (56.3)35 (31.8)< 0.001
3 à 4 foyers99 (46.5)24 (23.3)46 (41.8)< 0.001
Portal inflammation: Absent18 (8.5)11 (10.7)7 (6.4)0.32
Present195 (91.5)92 (89.3)103 (93.6)0.32
MASH: Present80 (37.6)32 (31.06)48 (43.63)0.06
Absent133 (62.4)71 (68.9)62 (56.4)0.06
Classification Metavir (activity): Stade A154 (25.4)34 (33.0)20 (18.2)< 0.001
Stade A2135 (63.4)66 (64.1)69 (62.7)< 0.001
Stade A324 (11.3)3 (2.9)21 (19.1)< 0.001
Classification Metavir (fibrosis): Stade F06 (2.8)5 (4.9)1 (0.9)< 0.001
Stade F129 (13.6)24 (23.3)5 (4.5)< 0.001
Stade F2144 (67.6)67 (65.0)77 (70)< 0.001
Stade F326 (12.2)5 (4.9)21 (19.1)< 0.001
Stade F48 (3.8)2 (1.9)6 (5.5)< 0.001
Stiffness (kPa) MED8.5 (5.3-24.5)7.69 (5.3-14.2)9.25 (7.2-24.5)< 0.001
CAP (dB/m) MED312.91 (180-400)300.85 (180-400)324.20 (224-400)< 0.001
Elasticity (m/second)1.11 (0.59-2.94)1.01 (0.59-2.14)1.20 (0.73-2.94)< 0.001
Steatosis (%)16.46 (3-50)14.22 (3-40)18.55 (4-50)< 0.001
Prevalence of MASLD

During the inclusion period, 345 people underwent Chx due to symptomatic gallstones. All patients had liver ultrasounds, and 140 were diagnosed with MASL, representing a frequency of 40.59%. One hundred and thirteen of the 317 people tested for liver morphology using FibroScan® were diagnosed with MASL, representing a 43.84% frequency. Two hundred forty-three patients underwent intraoperative LB. MASLD was found in 103 persons, with a prevalence of 42.38%. There was no significant difference between the two prevalence rates (P = 0.89).

Changes in steatosis and fibrosis

During the follow-up period, the MASL value in the CHx group significantly increased from M0 to M36 (P < 0.001), while the control group had a decrease (P = 0.013) (Table 3). The Chx group’s MASL biological scores improved from the beginning to the end of the study: FLI (75.67; 78.82), HSI (40.61; 42.02), and LAP (82.31; 93.79), respectively. The control group’s scores fell: FLI (81.15; 74.51), HSI (44.99; 42.01), and LAP (82.94; 69.99), all with P < 0.005 (Figure 2). The FibroScan® data revealed an increase in liver stiffness in the Chx group and a decrease in the control group (P = 0.002 and P < 0.001). The hepatic elasticity of the Chx group improved from the start to the end of the study, as evaluated by ARFI. The control group demonstrated a significant decrease (P < 0.001). The biological scores for liver fibrosis altered paradoxically between the start and end of the experiment in both groups (Figure 3); the changes were not statistically significant, with the exception of BARD and APRI (Figure 4).

Figure 2
Figure 2 Evolution of biological scores of hepatic steatosis. LAP: Lipid accumulation product; FLI: Fatty liver index; HSI: Hepatic steatosis index.
Figure 3
Figure 3 Evolution of liver fibrosis according to the exposure factor. ARFI: Acoustic radiation force fibrosis.
Figure 4
Figure 4 Evolution of biological scores of fibrosis according to the exposure factor. FIB4: Fibrosis 4; BARD: Body mass index, aspartate aminotransferase/alanine aminotransferase ratio, diabetes mellitus; APRI: Aspartate aminotransferase/platelet ratio index.
Table 3 Evolution of hepatic steatosis, mean ± SE.

M0
M36
P value M0 vs M36
CAP med (dB/m)Chx: Yes300.77 ± 47.42314.17 ± 44.700.013
Chx: No325.06 ± 41.74296.36 ± 56.51< 0.001
Graisse hepatique/IRM (%)Chx: Yes14.22 ± 8.6415.98 ± 7.93< 0.001
Chx: No18.55 ± 8.5713.88 ± 8.12< 0.001
Metabolic and anthropometric trends

The study revealed that the Chx group’s HOMA index test results decreased, while the control group improved (P < 0.001). Figure 5 shows that the BMI of the Chx group increased by 0.68 kg/m2, while the control group reduced by 0.78 kg/m2 (P < 0.001). The Chx group gained an average of 3.93 kg over the follow-up period. The control group experienced an average weight loss of 5.57 kg (P < 0.001). During the experiment, the Chx group’s waist circumference grew by 2.33 cm on average. The control group had an average reduction of 6.85 cm (P < 0.001). Figure 6 shows that the Chx group’s hepatic cytolysis worsened during the follow-up period, as demonstrated by an increase of 0.55 IU/L in ALT levels. The control group’s level decreased by 4.48 IU/L, with P values of 0.80 and 0.06.

Figure 5
Figure 5 Evolution of the homeostasis model assessment index according to the exposure factor. HOMA-IR: Homeostasis model assessment index.
Figure 6
Figure 6 Evolution of amino-transferases according to the exposure factor. ALT: Alanine aminotransferase.
Risk factor analysis

Individuals over the age of 50 with diabetes mellitus, GBS, Chx, weight, BMI, waist circumference, alanine amino transferase (ALAT), gamma-glutamyl transferase (GGT), hemoglobin A1c (HbA1c), HOMA test, FLI, HSI, fibrosis 4, ARFI elasticity, MRI steatosis, FibroScan elasticity, and CAP had an increased risk of S2 and steatosis. In a multivariate analysis, obesity, Chx, sphingomyelin, HbA1c, FLI, and MRI steatosis were identified as independent risk factors (Table 4). Diabetes mellitus, GBS, Chx, BMI, weight, waist circumference, sphingomyelin, ALAT, GGT, FLI, HSI, ARFI elasticity, MRI steatosis, FibroScan elasticity, CAP, and intima-media thickness were all linked to advanced fibrosis (F2 or above) in univariate analysis. The multivariate analysis revealed that Chx, BARD score, and FibroScan stiffness were independent risk variables (Table 5). Diabetes mellitus, GBS, Chx, ALAT, HSI, ARFI elasticity, MRI steatosis, FibroScan elasticity, and CAP were identified as MASH risk factors using univariate analysis. Obesity, Chx, GGT, MRI steatosis, and FibroScan elasticity were all identified as independent risk factors in the multivariate analysis (Table 6).

Table 4 Uni and multivariate analysis of risk factors associated with the presence of metabolic dysfunction-associated steatotic liver disease ≥ S2.
Risk factorUnivariate
Multivariate
OR
95%CI
P value
OR
95%CI
P value
Age ≥ 50 years0.310.13-0.700.0050.190.03-1.030.054
Sex female1.680.97-2.900.0621.400.52-3.700.86
High blood pressure0.850.49-1.470.570.670.87-4.320.57
Diabetes mellitus1.650.95-2.860.070.570.84-10.380.29
Hypertriglyceridemia1.090.48-2.500.820.670.54-2.890.33
Hypercholesterolemia0.980.35-2.740.970.780.45-4.230.42
Obesity0.890.51-1.570.711.320.98-4.120.005
GBS2.941.66-5.200.0000.340.78-1.220.66
Chx3.111.76-5.480.0001.120.89-3.210.04
weight0.960.94-0.980.010.980.45-3.210.57
BMI1.081.01-1.160.010.921.12-4.270.49
Hip circumference (cm)1.031.00-1.060.031.231.11-4.250.60
Waist size (cm)2.101.11-3.940.022.950.84-10.380.008
Chest perimeter (cm)2.861.53-5.320.0010.650.89-3.740.93
GGT1.380.77-2.460.270.870.65-5.120.90
Total cholesterol0.720.33-1.560.410.650.87-4.220.26
LDL cholesterol1.300.53-3.140.550.880.77-3.110.06
HbA1c1.230.67-1.470.011.931.11-5.230.038
BARD score0.570.27-1.180.130.650.55-2.110.35
Home test1.540.27-8.650.610.340.44-3.250.69
FLI score0.970.95-0.990.0052.871.69-6.340.047
LAP score1.400.39-4.950.590.990.89-4.110.23
HSI score1.081.03-1.120.0000.540.43-2.880.49
APRI score1.320.44-3.950.610.560.55-2.330.21
FIB4 score0.770.54-1.10.152.650.84-8.320.09
NFS score0.840.70-1.000.061.830.65-5.130.60
Elasticity/ultrasound3.521.53-8.060.0037.000.68-71.400.10
Steatosis/MRI1.271.19-1.360.00010.213.65-28.52< 0.001
Elasticity/FibroScan®1.311.11-1.550.0012.270.40-12.760.35
CAP1.011.00-1.020.0003.210.47-21.640.23
Table 5 Uni and multivariate analysis of risk factors associated with the presence of advanced fibrosis.
Risk factorUnivariate
Multivariate
OR
95%CI
P value
OR
95%CI
P value
Age ≥ 50 years1.310.58-2.930.660.920.88-2.670.60
Sex female0.730.41-1.290.280.450.33-1.650.88
High blood pressure0.890.50-1.580.70.89069-1.260.64
Diabetes mellitus0.420.23-0.770.0050.990.93-1.170.17
Hypertriglyceridemia1.10.35-2.220.861.350.65-2.310.08
Hypercholesterolemia1.560.55-4.390.851.791.89-2.910.09
Obesity0.580.31-1.070.080.980.33-3.010.52
GBS2.621.46-4.720.0000.990.87-1.050.99
Chx0.370.20-0.670.0002.691.55-2.880.04
weight0.960.94-0.980.0380.990.87-1.760.93
BMI0.910.86-0.970.010.86069-1.060.18
Waist size (cm)0.940.91-0.980.0120.990.92-1.070.62
Metabolic syndrome0.320.15-0.690.0040.510.16-1.640.26
ALT0.940.91-0.970.0030.990.23-3.010.79
GGT0.980.96-1.000.020.990.97-1.050.53
Triglycerides1.050.72-1.550.271.751.09-2.810.07
LDL Cholesterol1.240.83-1.870.221.320.99-2.430.09
BARD score1.120.79-1.590.301.780.99-2.670.03
Home test0.900.78-1.040.180.890.77-2.310.29
FLI score0.970.95-0.990.021.010.97-1.050.42
LAP score0.990.98-1.000.480.870.77-1.880.58
HSI score0.900.84-0.960.0000.960.85-1.070.48
APRI score1.730.01-2.220.1780.890.47-2.990.65
FIB4 score0.960.59-1.570.930.991.32-3.460.55
NFS score0.950.75-1.210.950.320.44-1.210.50
Elasticity/ultrasound0.0270.003-0.220.0002.654.27-1.650.09
Steatosis/MRI0.890.84-0.950.0000.130.03-0.580.712
Elasticity/FibroScan®0.090.04-0.200.0000.980.88-1.870.006
CAP0.990.98-1.000.0000.430.56-1.120.4
Table 6 Uni and multivariate analysis of risk factors associated with the presence of metabolic dysfunction-associated steatohepatitis.
Risk factorUnivariate
Multivariate
OR
95%CI
P value
OR
95%CI
P value
Age ≥ 50 years1.000.98-1.030.930.770.87-1.650.2
Sex female0.980.56-1.710.800.890.77-1.340.45
High blood pressure0.960.55-1.670.930.980.89-2.110.10
Diabetes mellitus0.500.28-0.890.011.030.87-1.220.69
Hypertriglyceridemia0.970.42-2.240.910.780.98-4.220.64
Hypercholesterolemia1.740.66-4.600.990.890.78-2.230.79
Obesity1.350.76-2.380.241.920.92-1.130.04
GBS0.580.33-1.020.040.670.77-1.110.056
Chx0.580.33-1.020.0591.430.87-1.370.05
weight0.990.97-1.010.760.780.66-1.210.89
BMI0.980.92-1.050.731.030.87-1.220.69
Waist size (cm)0.980.95-1.010.220.990.92-1.060.82
Metabolic syndrome2.041.06-3.930.071.400.45-4.360.55
ALT0.970.96-0.990.0020.600.20-1.780.68
GGT0.990.98-1.000.271.870.98-2.110.02
Triglycerides0.910.68-1.220.590.680.28-1.220.17
LDL Cholesterol0.940.69-1.270.920.560.69-3.360.47
BARD score1.180.91-1.530.270.790.54-2.860.06
Home test0.910.83-1.010.060.860.47-1.380.45
FLI score0.980.96-1.000.070.790.64-1.660.13
LAP score1.000.99-1.000.800.340.87-1.330.75
HSI score0.940.91-0.980.0060.780.88-1.650.76
APRI score0.500.15-1.630.300.880.98-3.220.97
FIB4 score1.140.78-1.660.530.560.67-1.330.24
NFS score1.040.87-1.250.500.760.54-2.660.76
Elasticity/ultrasound0.260.11-0.590.0010.890.77-1.760.16
Steatosis/MRI0.880.85-0.920.0001.890.99-1.26< 0.001
Elasticity/FibroScan®0.700.58-0.830.0001.651.22-3.670.043
CAP0.980.98-0.990.0001.451.17-3.250.121
DISCUSSION

Limited study has been conducted on the impact of Chx on MASLD patients. More epidemiological data and clinical research into the many signs of MASLD in African communities are needed. Africa has the lowest rate of MASLD in the general population. Multiple clinical trials have revealed varying prevalence[1,2,34-36]. The prevalence of MASLD can vary depending on the sensitivity of the detection method used. LB is the gold standard for diagnosis and severity assessment; nevertheless, it is restricted by inherent risks, impracticality, and, most importantly, the insignificance of its indications in MASLD[37,38]. Thus, non-invasive radiological imaging, notably hepatic ultrasonography, is the most effective way to detect MASL.

A recent meta-analysis of studies using hepatic ultrasonography or LB for diagnosis estimated the global regional distribution of non-invasive MASLD as follows: 23.4% in Asia, 23.7% in Europe, 31.8% in the Middle East, 24.1% in North America, 30.5% in South America, and 13.5% in Africa. Africa has the lowest frequency[1,2,4]. The meta-analysis included only two African studies with small sample sizes. Studies have employed ultrasound to find MASLD in 20% of 100 asymptomatic Sudanese patients, whereas others discovered an incidence of 4.5% in 44 Nigerians[35]. Generalizing these findings across all African nations is impossible, especially given the scarcity of prevalence statistics in our population[35].

In our study, the prevalence of MASLD revealed by ultrasound imaging was 40.59% among patients who had underwent Chx. The literature shows a comparable occurrence. In the United States, Ruhl and Everhart[39] discovered a prevalence of 48.4% in patients who had Chx, 34.4% in GBS carriers, and 17.9% in the control group. Wang et al[40] reported 46.9% in cholecystectomized patients and 38.1% in the control group in Asia. Kwak et al[41] reported a frequency of 41.9% in South Korea, compared to 41.3% in the control group. Latenstein et al conducted prospective research in the Netherlands with 4307 patients, finding a 42.7% prevalence of MASLD among those who underwent Chx.

There has been limited research on the prevalence of histological MASLD in Chx patients[42-47]. García-Monzón et al[43] discovered that 41.4% of patients with steatosis and 10.2% of patients with MASH had MASLD in her Spanish cohort, according to LB. Liew et al[44] discovered a prevalence of 35.5% MASL and 18% MASH. In a study of 95 individuals who underwent Chx in Turkey, 55% developed MASH[45]. Research conducted in Italy on 524 individuals who underwent Chx with intraoperative LB discovered a MASL frequency of 77%[46]. In our study, the incidence of MASL in cholecystectomized patients was 42.38%, while MASH was 9.25%.

The cohort’s mean age at diagnosis was 51.66 ± 11.97 years. According to available data, the average age of patients at diagnosis in the adult population ranges between 40 and 65 years. Individuals aged 50 and older comprised 79.33% of the cohort. The results showed that 59.16% of the sample was over the age of 50. The average age was 48.39 years (SD = 12.75) for males and 54.84 years (SD = 10.21) for females (P < 0.001). The literature has demonstrated this disparity[48-52].

The study discovered that 71.4% of the patients had MS, 47.9% had hypertension, and 48.8% had diabetes mellitus. Ninety-one percent of patients had a BMI higher than 25 kg/m2. Ninety-two percent of patients had waist circumferences greater than 102 millimeters for men and 88 centimeters for women. Most studies suggest that the average BMI is greater than 25 kg/m2[24,49,50,53,54], and higher than 27 kg/m2 in patients with diabetes[55-59]. Our dataset includes seven patients with a BMI of < 22 kg/m2, indicating a distinct type of MASL among those with a lean frame. Younossi et al[47] discovered a 10% prevalence of MASLD in persons with an average BMI of 22 kg/m2, known as MASLD of the lean subject.

In our study, 70.9% of patients showed elevated ALAT levels. Several studies in the general population revealed higher levels of ALAT[60-63]. ALT is sometimes employed as a screening test; however, its sensitivity is significantly lower than that of ultrasonography. An aspartate amino transferase/ALAT ratio greater than one may be used as a diagnostic criterion, especially in communities with little alcohol consumption.

Histological steatosis was discovered in 208 individuals (97.2%). 53.3% of patients were classed as S1 and 37.9% as S2. 86% of the patients showed a combination of micro- and macro-vacuolar steatosis. The average percentage of steatosis was 29.53% ± 18.56%. MASH was identified in 80 patients, with a total frequency of 37.4%. Following inclusion, the Metavir fibrosis score categorized 80 patients (84.97%) as F0F2, whereas the activity evaluation classified 63.38% as stage A2.

This prospective study discovered that Chx is associated with a significant increase in liver fat, as evidenced by MS’s markers such as anthropometric measurements, lipid profiles, and the HOMA index. The findings support prior research, indicating that Chx effectively treats GBS and reduces the risk of gallbladder cancer. However, it may have negative metabolic consequences[20,64], potentially causing the onset or exacerbation of insulin resistance and its associated effects. The gastrointestinal tract can affect whole-body infrared sensitivity either directly, through signaling components released by its mucosa, or indirectly, by altering bile acid mass flow via the enterohepatic system and systemic circulation during rapid eating cycles. The gallbladder may produce FGF19, which leads to the sickness. The gallbladder mucosa produces more of this ileal hormone, which regulates bile acid production and gallbladder filling before being secreted into the bile[64]. FGF19 has a direct metabolic effect on lipid and glucose metabolism[65]. Patients with MASLD have reduced blood levels of FGF19 after Chx therapy[66]. Thus, dysregulation of FGF19 following Chx could help explain the metabolic consequences identified in our study.

In our study, two groups that followed identical hygienic-dietary protocols with comparable compliance saw a paradoxical progression. After 36 months of follow-up, individuals who had Chx gained an average of 4 kg and raised their BMI by 1.4 kg/m2. Ali et al[67] conducted a three-year follow-up study with two cohorts: 42 patients who underwent Chx and 42 participants in the control group. The weight gain was 5 kg, and the BMI rose by 2.1 points. Cortés et al[68] reported a weight gain of 4.1 kg in two years. During the 24-month follow-up, the control group dropped an average of 5.57 kg. Insulin resistance, defined as a HOMA index more than 2.53, was seen in almost all patients at the time of enrollment. The HOMA index score in the Chx group rose from 7.36 ± 2.52 to 8.78 ± 3.19 (P < 0.001). The control group saw a significant decrease in this index, from 8.32 ± 3.20 to 6.00 ± 2.43 (P < 0.001). Cortes et al[68] discovered that the HOMA index increased from 1.31 to 2.2 during the period of 36 months. Nutritional and metabolic parameters point to a decrease in diabetes mellitus among Chx patients.

In the Chx population, the median CAP increased from 300.77 dB/m to 314.17 dB/m (P < 0.013) after an average follow-up of 36 months. The median in the control group decreased from 325.06 to 296.36 (P < 0.001). The study indicated that the average beginning fat percentage increased from 14.22% to 15.98% toward the end (P < 0.001). Cortes discovered a rise from 5.4% to 5.8% after a 24-month follow-up[68]. Steatosis-related biological markers, including the FLI, HSI, and LAP, increased. The cohort that underwent Chx exhibited changes from 75.67 to 81.54, 40.61 to 43.64, and 82.31 to 108.41. A statistically significant difference was discovered (P < 0.001). In comparison, the control group experienced a significant decline in patient assessments (P < 0.001). The biological ratings support the morphological data obtained from FibroScan® and MRI.

Longitudinal investigations in Western and Asian populations have found a robust connection between Chx and MASLD[40,47]. Wang et al[40] discovered that the prevalence of MASLD was higher in the Chx group, when accounting for risk variables in the multivariate analysis, the difference became insignificant. The findings can be attributable to the study’s retrospective design and the absence of an investigation of confounding variables such as alcohol intake, smoking, physical activity, and the kind of surgery performed (laparoscopic or conventional).

The literature is deficient in investigations on the progression of fibrosis. The mechanisms that explain the progression from simple steatosis to fibrosis and its implications also account for the rise in fibrosis in this patient cohort, which is expected to worsen. Patients in the Chx group experienced a median increase in FibroScan® stiffness from 7.67 kPa to 8.38 kPa over 36 months (P = 0.002). The median in the non- Chx group decreased from 9.25 km/h to 7.60 km/h (P < 0.001). After a 36-month follow-up, the cholecystectomized group’s average elasticity increased from 1.01 m/second to 1.12 m/second (P < 0.001). The Chx group’s biological scores for fibrosis, BARD, fibrosis 4, APRI, and NFS rose from the beginning to the end of the experiment, showing that the fibrosis had deteriorated. With the exception of the APRI score, the difference was minimal. The control group had significant score improvements, with P values less than 0.001 for all four categories. The results shed light on the course of sickness in the control group. This is the first study on the progression of fibrosis. Verifying the results with sequential LB would be intriguing, as histology is a major characteristic of MASLD.

Over a 21-year follow-up period, this study examined National Health and Nutrition Examination Survey data to assess the risk of hospital admission or mortality due to cirrhosis in patients with a history of Chx (n = 466) vs those without surgery (n = 8691). Individuals who had a previous Chx were more likely to be hospitalized or die from cirrhosis [odds ratio (OR): 2.1, 95% confidence interval (CI): 1.1-4.0], and had a higher risk of elevated blood ALT (OR 1.8, 95%CI: 1.3-2.5) or GGT (OR: 1.7, 95%CI: 1.1-2.6) than those who had not undergone a Chx[69].

The major purpose of this study was also to evaluate the numerous risk factors linked with MASLD throughout the cohort. A multivariate study revealed that Chx, MRI-assessed fat volume, MS, FLI score, obesity, APRI score, and HbA1c levels are risk factors for S2 hepatic steatosis. Fan et al[70] examined 3175 patients and discovered a substantial link between morphological steatosis and factors such as male sex, diabetes mellitus, hypertension, BMI, waist circumference, triglycerides, high-density lipoprotein cholesterol, and fasting blood glucose. In a study of 133 individuals, Angulo et al[52] discovered that MASLD is associated with age, BMI, diabetes, and the ALAT/aspartate amino transferase ratio.

Our study indicated that advanced fibrosis > F2 was associated with ALT levels, FibroScan® elasticity, Chx, BARD score, and low density lipoprotein cholesterol levels. In a study of 102 diabetics with MASLD, Mansour et al[71] employed multivariate analysis to identify waist circumference, C-peptide, and AST levels as risk factors for severe fibrosis. Fracanzani et al[46] discovered a substantial link between advanced fibrosis and age, gender, BMI, ALT, ferritin, fasting blood glucose, and Homa index in their Italian study. In a meta-analysis, Argo et al[72] discovered that age and inflammatory activity at the first LB were linked to fibrosis progression. In a study of 60 patients who obtained two liver biopsies over an 8.4-year period, including those with initial MASH, Hagström et al[73] found no risk variables associated with the progression or onset of severe fibrosis.

Multivariate study in our patients identifies parameters associated with MASH lesions at LB, including FibroScan® elasticity, MRI fat amount, GGT levels, Chx, and obesity. After multivariate analysis of a cohort of 215 consecutive patients’ candidates for Chx who underwent LB and ultrasound, Nguyen and El-Serag[53] discovered the Homa test and the presence of steatosis on ultrasound to be predictive indications for MASH. Fracanzani et al[46] evaluated 458 patients in Italy and found two factors associated with MASH using multivariate analysis: Diabetes mellitus and ALT levels.

This study had limitations. The two groups were heterogeneous, with significant variations in several characteristics favoring the control group (weight, BMI, and fibrosis severity). In the absence of a control group, non-MASLD patients who had not undergone Chx were included. In practice, it may be difficult to keep these patients for long periods of time. The study is monocentric, with a single operator carrying out all assessments (FibroScan®, ARFI, MRI, and histological analysis) independently and without inter-operator comparison. The primary advantage of this study is its prospective design, which lasts 36 months and ensures the quality and completeness of the gathered data. Our study also included persons who had MASLD, as confirmed by histological examination. All patients were treated to a thorough evaluation and continued follow-up in accordance with the described process until the study was completed. Unlike most retrospective studies, ours has a prospective design and employs rigorous morphological (FibroScan®, ARFI, and MRI) and biochemical (fibrosis and steatosis scores, HOMA index) protocols for comparison.

CONCLUSION

Chx causes insulin resistance, increases the saturated hydrocarbon ratio, and worsens heart failure. Morphological evaluations and biological measurements provide strong support for these conclusions. S2 MASL is linked to six factors, including MRI fat, MS, and the FLI score, whereas advanced fibrosis is linked to the BARD score, FibroScan® elasticity, and Chx. MASH lesions are linked to FibroScan® elasticity, obesity, Chx, GGT, and MRI fat volume. We want to uncover risk factors associated with higher steatosis, advanced fibrosis, and MASH lesions in patients receiving Chx for symptomatic biliary disease by doing a comprehensive evaluation to reveal underlying MASLD. According to Chx, a surgical LB is neither risky nor unnecessary; it enables for histological diagnosis of the disease and serves as a reference for follow-up and future management of targeted patients. Patients undergoing Chx must adhere to dietary guidelines and engage in regular, specific physical activity.

References
1.  Vernon G, Baranova A, Younossi ZM. Systematic review: the epidemiology and natural history of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in adults. Aliment Pharmacol Ther. 2011;34:274-285.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 2462]  [Cited by in RCA: 2282]  [Article Influence: 152.1]  [Reference Citation Analysis (5)]
2.  Younossi ZM, Golabi P, de Avila L, Paik JM, Srishord M, Fukui N, Qiu Y, Burns L, Afendy A, Nader F. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: A systematic review and meta-analysis. J Hepatol. 2019;71:793-801.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 1890]  [Cited by in RCA: 1684]  [Article Influence: 240.6]  [Reference Citation Analysis (4)]
3.  Satapathy SK, Sanyal AJ. Epidemiology and Natural History of Nonalcoholic Fatty Liver Disease. Semin Liver Dis. 2015;35:221-235.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 272]  [Cited by in RCA: 247]  [Article Influence: 22.5]  [Reference Citation Analysis (1)]
4.  Argo CK, Caldwell SH. Epidemiology and natural history of non-alcoholic steatohepatitis. Clin Liver Dis. 2009;13:511-531.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 322]  [Cited by in RCA: 281]  [Article Influence: 16.5]  [Reference Citation Analysis (0)]
5.  Bellentani S. The epidemiology of non-alcoholic fatty liver disease. Liver Int. 2017;37 Suppl 1:81-84.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 502]  [Cited by in RCA: 450]  [Article Influence: 50.0]  [Reference Citation Analysis (1)]
6.  Iqbal U, Perumpail BJ, Akhtar D, Kim D, Ahmed A. The Epidemiology, Risk Profiling and Diagnostic Challenges of Nonalcoholic Fatty Liver Disease. Medicines (Basel). 2019;6:41.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 53]  [Cited by in RCA: 75]  [Article Influence: 10.7]  [Reference Citation Analysis (5)]
7.  Houti L, Hamani-Medjaoui I, Ouhaibi-Djellouli H, Lardjam-Hetraf SA, Mediene-Benchekor S. Obésité, activité physique et habitudes nutritionnelles dans la population urbaine de l’Ouest Algérien. Nutr Clin Metab. 2018;32:308.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 1]  [Cited by in RCA: 2]  [Article Influence: 0.3]  [Reference Citation Analysis (0)]
8.  Fedala N, Mekimene L, Mokhtari M, Haddam AEM, Fedala NS, Kardjadj M. Prevalence and risk factors of overweight and obesity among schoolchildren and adolescents in Algiers. Medit J Nutr Metab. 2017;10:105-112.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in RCA: 1]  [Reference Citation Analysis (0)]
9.  Jaruvongvanich V, Sanguankeo A, Upala S. Significant Association Between Gallstone Disease and Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis. Dig Dis Sci. 2016;61:2389-2396.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 54]  [Cited by in RCA: 49]  [Article Influence: 4.9]  [Reference Citation Analysis (0)]
10.  Jaruvongvanich V, Sanguankeo A, Jaruvongvanich S, Upala S. Association Between Cholecystectomy and Nonalcoholic Fatty Liver Disease: A Meta-analysis. World J Surg. 2016;40:2816-2817.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 6]  [Cited by in RCA: 11]  [Article Influence: 1.2]  [Reference Citation Analysis (0)]
11.  Chang Y, Noh YH, Suh BS, Kim Y, Sung E, Jung HS, Kim CW, Kwon MJ, Yun KE, Noh JW, Shin H, Cho YK, Ryu S. Bidirectional Association between Nonalcoholic Fatty Liver Disease and Gallstone Disease: A Cohort Study. J Clin Med. 2018;7:458.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 12]  [Cited by in RCA: 40]  [Article Influence: 5.0]  [Reference Citation Analysis (0)]
12.  Tana C, Ballestri S, Ricci F, Di Vincenzo A, Ticinesi A, Gallina S, Giamberardino MA, Cipollone F, Sutton R, Vettor R, Fedorowski A, Meschi T. Cardiovascular Risk in Non-Alcoholic Fatty Liver Disease: Mechanisms and Therapeutic Implications. Int J Environ Res Public Health. 2019;16:3104.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 159]  [Cited by in RCA: 140]  [Article Influence: 20.0]  [Reference Citation Analysis (0)]
13.  Lonardo A, Lombardini S, Scaglioni F, Ballestri S, Verrone AM, Bertolotti M, Carulli L, Ganazzi D, Carulli N, Loria P. Fatty liver, carotid disease and gallstones: a study of age-related associations. World J Gastroenterol. 2006;12:5826-5833.  [PubMed]  [DOI]  [Full Text]
14.  Liu J, Lin H, Zhang C, Wang L, Wu S, Zhang D, Tang F, Xue F, Liu Y. Non-alcoholic fatty liver disease associated with gallstones in females rather than males: a longitudinal cohort study in Chinese urban population. BMC Gastroenterol. 2014;14:213.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 23]  [Cited by in RCA: 34]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
15.  Shen C, Wu X, Xu C, Yu C, Chen P, Li Y. Association of cholecystectomy with metabolic syndrome in a Chinese population. PLoS One. 2014;9:e88189.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 43]  [Cited by in RCA: 47]  [Article Influence: 3.9]  [Reference Citation Analysis (0)]
16.  Martin DJ, Weideman R, Crook T, Brown G. Relationship of hepatic fibrosis, cirrhosis, and mortality with cholecystectomy in patients with hepatitis C virus infection. Eur J Gastroenterol Hepatol. 2016;28:181-186.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 2]  [Cited by in RCA: 7]  [Article Influence: 0.7]  [Reference Citation Analysis (0)]
17.  Yun S, Choi D. Association Between Cholecystectomy and Nonalcoholic Fatty Liver Disease: A Meta-analysis: Reply. World J Surg. 2016;40:2818-2819.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 1]  [Cited by in RCA: 3]  [Article Influence: 0.3]  [Reference Citation Analysis (0)]
18.  Malagelada JR, Go VL, Summerskill WH, Gamble WS. Bile acid secretion and biliary bile acid composition altered by cholecystectomy. Am J Dig Dis. 1973;18:455-459.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 110]  [Cited by in RCA: 113]  [Article Influence: 2.1]  [Reference Citation Analysis (0)]
19.  Cortés V, Amigo L, Zanlungo S, Galgani J, Robledo F, Arrese M, Bozinovic F, Nervi F. Metabolic effects of cholecystectomy: gallbladder ablation increases basal metabolic rate through G-protein coupled bile acid receptor Gpbar1-dependent mechanisms in mice. PLoS One. 2015;10:e0118478.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 15]  [Cited by in RCA: 27]  [Article Influence: 2.5]  [Reference Citation Analysis (0)]
20.  Zanlungo S, Rigotti A, Francisco Miquel J, Nervi F. Abnormalities of lipid metabolism, gallstone disease and gallbladder function. Clin Lipidol. 2011;6:315-325.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 5]  [Cited by in RCA: 6]  [Article Influence: 0.4]  [Reference Citation Analysis (0)]
21.  Amigo L, Husche C, Zanlungo S, Lütjohann D, Arrese M, Miquel JF, Rigotti A, Nervi F. Cholecystectomy increases hepatic triglyceride content and very-low-density lipoproteins production in mice. Liver Int. 2011;31:52-64.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 53]  [Cited by in RCA: 67]  [Article Influence: 4.5]  [Reference Citation Analysis (0)]
22.  Cheng D, Xu X, Simon T, Boudyguina E, Deng Z, VerHague M, Lee AH, Shelness GS, Weinberg RB, Parks JS. Very Low Density Lipoprotein Assembly Is Required for cAMP-responsive Element-binding Protein H Processing and Hepatic Apolipoprotein A-IV Expression. J Biol Chem. 2016;291:23793-23803.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 15]  [Cited by in RCA: 18]  [Article Influence: 1.8]  [Reference Citation Analysis (0)]
23.  Wahlin T, Bloom GD, Carlsöö B, Rhodin L. Effects of fasting and refeeding on secretory granules of the mouse gallbladder epithelium. A quantitative electron microscopic study. Gastroenterology. 1976;70:353-358.  [PubMed]  [DOI]
24.  Péan N, Doignon I, Garcin I, Besnard A, Julien B, Liu B, Branchereau S, Spraul A, Guettier C, Humbert L, Schoonjans K, Rainteau D, Tordjmann T. The receptor TGR5 protects the liver from bile acid overload during liver regeneration in mice. Hepatology. 2013;58:1451-1460.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 169]  [Cited by in RCA: 153]  [Article Influence: 11.8]  [Reference Citation Analysis (0)]
25.  European Association for the Study of the Liver (EASL); European Association for the Study of Diabetes (EASD);  European Association for the Study of Obesity (EASO). EASL-EASD-EASO Clinical Practice Guidelines for the management of non-alcoholic fatty liver disease. J Hepatol. 2016;64:1388-1402.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 3686]  [Cited by in RCA: 3313]  [Article Influence: 331.3]  [Reference Citation Analysis (7)]
26.  Wong VW, Vergniol J, Wong GL, Foucher J, Chan HL, Le Bail B, Choi PC, Kowo M, Chan AW, Merrouche W, Sung JJ, de Lédinghen V. Diagnosis of fibrosis and cirrhosis using liver stiffness measurement in nonalcoholic fatty liver disease. Hepatology. 2010;51:454-462.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 1098]  [Cited by in RCA: 988]  [Article Influence: 61.8]  [Reference Citation Analysis (13)]
27.  Kwok R, Tse YK, Wong GL, Ha Y, Lee AU, Ngu MC, Chan HL, Wong VW. Systematic review with meta-analysis: non-invasive assessment of non-alcoholic fatty liver disease--the role of transient elastography and plasma cytokeratin-18 fragments. Aliment Pharmacol Ther. 2014;39:254-269.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 344]  [Cited by in RCA: 297]  [Article Influence: 24.8]  [Reference Citation Analysis (3)]
28.  Tovo CV, Villela-Nogueira CA, Leite NC, Panke CL, Port GZ, Fernandes S, Buss C, Coral GP, Cardoso AC, Cravo CM, Calçado FL, Rezende GFM, Ferreira FC, Araujo-Neto JM, Perez RM, Moraes-Coelho HS, de Mattos AA. Transient hepatic elastography has the best performance to evaluate liver fibrosis in non-alcoholic fatty liver disease (NAFLD). Ann Hepatol. 2019;18:445-449.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 26]  [Cited by in RCA: 30]  [Article Influence: 4.3]  [Reference Citation Analysis (4)]
29.  Wong VW, Wong GL, Chim AM, Tse AM, Tsang SW, Hui AY, Choi PC, Chan AW, So WY, Chan FK, Sung JJ, Chan HL. Validation of the NAFLD fibrosis score in a Chinese population with low prevalence of advanced fibrosis. Am J Gastroenterol. 2008;103:1682-1688.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 17]  [Cited by in RCA: 39]  [Article Influence: 2.2]  [Reference Citation Analysis (0)]
30.  Nobili V, Parkes J, Bottazzo G, Marcellini M, Cross R, Newman D, Vizzutti F, Pinzani M, Rosenberg WM. Performance of ELF serum markers in predicting fibrosis stage in pediatric non-alcoholic fatty liver disease. Gastroenterology. 2009;136:160-167.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 214]  [Cited by in RCA: 197]  [Article Influence: 11.6]  [Reference Citation Analysis (0)]
31.  Sasso M, Beaugrand M, de Ledinghen V, Douvin C, Marcellin P, Poupon R, Sandrin L, Miette V. Controlled attenuation parameter (CAP): a novel VCTE™ guided ultrasonic attenuation measurement for the evaluation of hepatic steatosis: preliminary study and validation in a cohort of patients with chronic liver disease from various causes. Ultrasound Med Biol. 2010;36:1825-1835.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 743]  [Cited by in RCA: 665]  [Article Influence: 41.6]  [Reference Citation Analysis (3)]
32.  Liu H, Fu J, Hong R, Liu L, Li F. Acoustic Radiation Force Impulse Elastography for the Non-Invasive Evaluation of Hepatic Fibrosis in Non-Alcoholic Fatty Liver Disease Patients: A Systematic Review & Meta-Analysis. PLoS One. 2015;10:e0127782.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 87]  [Cited by in RCA: 77]  [Article Influence: 7.0]  [Reference Citation Analysis (0)]
33.  Permutt Z, Le TA, Peterson MR, Seki E, Brenner DA, Sirlin C, Loomba R. Correlation between liver histology and novel magnetic resonance imaging in adult patients with non-alcoholic fatty liver disease - MRI accurately quantifies hepatic steatosis in NAFLD. Aliment Pharmacol Ther. 2012;36:22-29.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 314]  [Cited by in RCA: 292]  [Article Influence: 20.9]  [Reference Citation Analysis (1)]
34.  Ahmed MH, Noor SK, Bushara SO, Husain NE, Elmadhoun WM, Ginawi IA, Osman MM, Mahmoud AO, Almobarak AO. Non-Alcoholic Fatty Liver Disease in Africa and Middle East: An Attempt to Predict the Present and Future Implications on the Healthcare System. Gastroenterology Res. 2017;10:271-279.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 36]  [Cited by in RCA: 33]  [Article Influence: 3.7]  [Reference Citation Analysis (0)]
35.  Organisation mondiale de la Santé  Enquête nationale sur la mesure du poids des facteurs de risque des Maladies Non Transmissibles selon l’approche STEPwise de l’OMS Principaux résultats. [cited 3 August 2025]. Available from: https://www.afro.who.int/fr/publications/enquete-nationale-sur-la-mesure-du-poids-des-facteurs-de-risque-des-maladies-non.  [PubMed]  [DOI]
36.  El Rhazi K  Transition nutritionnelle, facteurs associés et émergence des maladies chroniques au Maroc: étude transversale en population générale adulte. M.Sc. Thesis, Université Sidi Mohamed ben Abdellah. 2010. Available from: https://theses.fr/2010BOR21751.  [PubMed]  [DOI]
37.  Anty R, Gual P. [Pathogenesis of non-alcoholic fatty liver disease]. Presse Med. 2019;48:1468-1483.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 13]  [Cited by in RCA: 17]  [Article Influence: 2.4]  [Reference Citation Analysis (0)]
38.  Bedossa P, Patel K. Biopsy and Noninvasive Methods to Assess Progression of Nonalcoholic Fatty Liver Disease. Gastroenterology. 2016;150:1811-1822.e4.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 102]  [Cited by in RCA: 96]  [Article Influence: 9.6]  [Reference Citation Analysis (0)]
39.  Ruhl CE, Everhart JE. Relationship of non-alcoholic fatty liver disease with cholecystectomy in the US population. Am J Gastroenterol. 2013;108:952-958.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 77]  [Cited by in RCA: 115]  [Article Influence: 8.8]  [Reference Citation Analysis (1)]
40.  Wang HG, Wang LZ, Fu HJ, Shen P, Huang XD, Zhang FM, Xie R, Yang XZ, Ji GZ. Cholecystectomy does not significantly increase the risk of fatty liver disease. World J Gastroenterol. 2015;21:3614-3618.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in CrossRef: 7]  [Cited by in RCA: 14]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
41.  Kwak MS, Kim D, Chung GE, Kim W, Kim YJ, Yoon JH. Cholecystectomy is independently associated with nonalcoholic fatty liver disease in an Asian population. World J Gastroenterol. 2015;21:6287-6295.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in CrossRef: 59]  [Cited by in RCA: 63]  [Article Influence: 5.7]  [Reference Citation Analysis (4)]
42.  Latenstein CSS, Alferink LJM, Darwish Murad S, Drenth JPH, van Laarhoven CJHM, de Reuver PR. The Association Between Cholecystectomy, Metabolic Syndrome, and Nonalcoholic Fatty Liver Disease: A Population-Based Study. Clin Transl Gastroenterol. 2020;11:e00170.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 3]  [Cited by in RCA: 29]  [Article Influence: 5.8]  [Reference Citation Analysis (0)]
43.  García-Monzón C, Vargas-Castrillón J, Porrero JL, Alonso MT, Bonachía O, Castillo MJ, Marcos A, Quirós E, Ramos B, Sánchez-Cabezudo C, Villar S, Sáez A, Rodríguez de Cía J, del Pozo E, Vega-Piris L, Soto-Fernández S, Lo Iacono O, Miquilena-Colina ME. Prevalence and risk factors for biopsy-proven non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in a prospective cohort of adult patients with gallstones. Liver Int. 2015;35:1983-1991.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 19]  [Cited by in RCA: 24]  [Article Influence: 2.2]  [Reference Citation Analysis (0)]
44.  Liew PL, Lee WJ, Wang W, Lee YC, Chen WY, Fang CL, Huang MT. Fatty liver disease: predictors of nonalcoholic steatohepatitis and gallbladder disease in morbid obesity. Obes Surg. 2008;18:847-853.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 41]  [Cited by in RCA: 40]  [Article Influence: 2.2]  [Reference Citation Analysis (0)]
45.  Yener O, Aksoy F, Demır M, Özçelık A, Erengül C. Gallstones associated with nonalcoholic steatohepatitis (NASH) and metabolic syndrome. Turk J Gastroenterol. 2010;21:411-415.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 20]  [Cited by in RCA: 18]  [Article Influence: 1.1]  [Reference Citation Analysis (0)]
46.  Fracanzani AL, Valenti L, Russello M, Miele L, Bertelli C, Bellia A, Masetti C, Cefalo C, Grieco A, Marchesini G, Fargion S. Gallstone disease is associated with more severe liver damage in patients with non-alcoholic fatty liver disease. PLoS One. 2012;7:e41183.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 54]  [Cited by in RCA: 52]  [Article Influence: 3.7]  [Reference Citation Analysis (0)]
47.  Younossi ZM, Stepanova M, Negro F, Hallaji S, Younossi Y, Lam B, Srishord M. Nonalcoholic fatty liver disease in lean individuals in the United States. Medicine (Baltimore). 2012;91:319-327.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 441]  [Cited by in RCA: 410]  [Article Influence: 29.3]  [Reference Citation Analysis (5)]
48.  Williams CD, Stengel J, Asike MI, Torres DM, Shaw J, Contreras M, Landt CL, Harrison SA. Prevalence of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis among a largely middle-aged population utilizing ultrasound and liver biopsy: a prospective study. Gastroenterology. 2011;140:124-131.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 1760]  [Cited by in RCA: 1613]  [Article Influence: 107.5]  [Reference Citation Analysis (1)]
49.  Fan JG, Zhu J, Li XJ, Chen L, Li L, Dai F, Li F, Chen SY. Prevalence of and risk factors for fatty liver in a general population of Shanghai, China. J Hepatol. 2005;43:508-514.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 321]  [Cited by in RCA: 302]  [Article Influence: 14.4]  [Reference Citation Analysis (14)]
50.  Hu X, Huang Y, Bao Z, Wang Y, Shi D, Liu F, Gao Z, Yu X. Prevalence and factors associated with nonalcoholic fatty liver disease in Shanghai work-units. BMC Gastroenterol. 2012;12:123.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 75]  [Cited by in RCA: 75]  [Article Influence: 5.4]  [Reference Citation Analysis (0)]
51.  Eguchi Y, Hyogo H, Ono M, Mizuta T, Ono N, Fujimoto K, Chayama K, Saibara T; JSG-NAFLD. Prevalence and associated metabolic factors of nonalcoholic fatty liver disease in the general population from 2009 to 2010 in Japan: a multicenter large retrospective study. J Gastroenterol. 2012;47:586-595.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 452]  [Cited by in RCA: 406]  [Article Influence: 29.0]  [Reference Citation Analysis (1)]
52.  Angulo P, Keach JC, Batts KP, Lindor KD. Independent predictors of liver fibrosis in patients with nonalcoholic steatohepatitis. Hepatology. 1999;30:1356-1362.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 1213]  [Cited by in RCA: 1063]  [Article Influence: 39.4]  [Reference Citation Analysis (0)]
53.  Nguyen DM, El-Serag HB. The epidemiology of obesity. Gastroenterol Clin North Am. 2010;39:1-7.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 419]  [Cited by in RCA: 374]  [Article Influence: 23.4]  [Reference Citation Analysis (0)]
54.  Júnior WS, Nonino-Borges CB. Clinical predictors of different grades of nonalcoholic fatty liver disease. Obes Surg. 2012;22:248-252.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 10]  [Cited by in RCA: 11]  [Article Influence: 0.7]  [Reference Citation Analysis (0)]
55.  Singh S, Allen AM, Wang Z, Prokop LJ, Murad MH, Loomba R. Fibrosis progression in nonalcoholic fatty liver vs nonalcoholic steatohepatitis: a systematic review and meta-analysis of paired-biopsy studies. Clin Gastroenterol Hepatol. 2015;13:643-54.e1.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 1438]  [Cited by in RCA: 1321]  [Article Influence: 120.1]  [Reference Citation Analysis (6)]
56.  Portillo-Sanchez P, Bril F, Maximos M, Lomonaco R, Biernacki D, Orsak B, Subbarayan S, Webb A, Hecht J, Cusi K. High Prevalence of Nonalcoholic Fatty Liver Disease in Patients With Type 2 Diabetes Mellitus and Normal Plasma Aminotransferase Levels. J Clin Endocrinol Metab. 2015;100:2231-2238.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 431]  [Cited by in RCA: 399]  [Article Influence: 36.3]  [Reference Citation Analysis (4)]
57.  Rocha R, Cotrim HP, Carvalho FM, Siqueira AC, Braga H, Freitas LA. Body mass index and waist circumference in non-alcoholic fatty liver disease. J Hum Nutr Diet. 2005;18:365-370.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 70]  [Cited by in RCA: 69]  [Article Influence: 3.3]  [Reference Citation Analysis (3)]
58.  Chalasani N, Younossi Z, Lavine JE, Charlton M, Cusi K, Rinella M, Harrison SA, Brunt EM, Sanyal AJ. The diagnosis and management of nonalcoholic fatty liver disease: Practice guidance from the American Association for the Study of Liver Diseases. Hepatology. 2018;67:328-357.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 5962]  [Cited by in RCA: 5324]  [Article Influence: 665.5]  [Reference Citation Analysis (5)]
59.  Harrison SA, Fecht W, Brunt EM, Neuschwander-Tetri BA. Orlistat for overweight subjects with nonalcoholic steatohepatitis: A randomized, prospective trial. Hepatology. 2009;49:80-86.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 375]  [Cited by in RCA: 335]  [Article Influence: 19.7]  [Reference Citation Analysis (3)]
60.  Verma S, Jensen D, Hart J, Mohanty SR. Predictive value of ALT levels for non-alcoholic steatohepatitis (NASH) and advanced fibrosis in non-alcoholic fatty liver disease (NAFLD). Liver Int. 2013;33:1398-1405.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 269]  [Cited by in RCA: 251]  [Article Influence: 19.3]  [Reference Citation Analysis (0)]
61.  Chen ZW, Chen LY, Dai HL, Chen JH, Fang LZ. Relationship between alanine aminotransferase levels and metabolic syndrome in nonalcoholic fatty liver disease. J Zhejiang Univ Sci B. 2008;9:616-622.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 58]  [Cited by in RCA: 69]  [Article Influence: 4.1]  [Reference Citation Analysis (0)]
62.  López-Amador N, Nolasco-Hipolito C, de J Rojas-Jimeno M, Carvajal- Zarrabal O. Liver enzymes in patients diagnosed with non-alcoholic fatty liver disease (NAFLD) in Veracruz: a comparative analysis with the literature. Clin Investig. 2017;07:011-016.  [PubMed]  [DOI]  [Full Text]
63.  Housset C, Chrétien Y, Debray D, Chignard N. Functions of the Gallbladder. Compr Physiol. 2016;6:1549-1577.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 69]  [Cited by in RCA: 123]  [Article Influence: 12.3]  [Reference Citation Analysis (0)]
64.  Ahmed MH, Ali A. Nonalcoholic fatty liver disease and cholesterol gallstones: which comes first? Scand J Gastroenterol. 2014;49:521-527.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 24]  [Cited by in RCA: 32]  [Article Influence: 2.7]  [Reference Citation Analysis (0)]
65.  Barrera F, Azócar L, Molina H, Schalper KA, Ocares M, Liberona J, Villarroel L, Pimentel F, Pérez-Ayuso RM, Nervi F, Groen AK, Miquel JF. Effect of cholecystectomy on bile acid synthesis and circulating levels of fibroblast growth factor 19. Ann Hepatol. 2015;14:710-721.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 46]  [Cited by in RCA: 57]  [Article Influence: 5.2]  [Reference Citation Analysis (0)]
66.  Lundåsen T, Gälman C, Angelin B, Rudling M. Circulating intestinal fibroblast growth factor 19 has a pronounced diurnal variation and modulates hepatic bile acid synthesis in man. J Intern Med. 2006;260:530-536.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 306]  [Cited by in RCA: 330]  [Article Influence: 16.5]  [Reference Citation Analysis (0)]
67.  Ali RB, Cahill RA, Watson RG. Weight gain after laparoscopic cholecystectomy. Ir J Med Sci. 2004;173:9-12.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 15]  [Cited by in RCA: 19]  [Article Influence: 0.9]  [Reference Citation Analysis (0)]
68.  Cortés V, Quezada N, Uribe S, Arrese M, Nervi F. Effect of cholecystectomy on hepatic fat accumulation and insulin resistance in non-obese Hispanic patients: a pilot study. Lipids Health Dis. 2017;16:129.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 16]  [Cited by in RCA: 29]  [Article Influence: 3.2]  [Reference Citation Analysis (0)]
69.  Ioannou GN. Cholelithiasis, cholecystectomy, and liver disease. Am J Gastroenterol. 2010;105:1364-1373.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 27]  [Cited by in RCA: 30]  [Article Influence: 1.9]  [Reference Citation Analysis (0)]
70.  Fan JG, Zhu J, Li XJ, Chen L, Lu YS, Li L, Dai F, Li F, Chen SY. Fatty liver and the metabolic syndrome among Shanghai adults. J Gastroenterol Hepatol. 2005;20:1825-1832.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 140]  [Cited by in RCA: 135]  [Article Influence: 6.4]  [Reference Citation Analysis (1)]
71.  Mansour A, Mohajeri-Tehrani MR, Samadi M, Gerami H, Qorbani M, Bellissimo N, Poustchi H, Hekmatdoost A. Risk factors for non-alcoholic fatty liver disease-associated hepatic fibrosis in type 2 diabetes patients. Acta Diabetol. 2019;56:1199-1207.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 23]  [Cited by in RCA: 24]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
72.  Argo CK, Northup PG, Al-Osaimi AM, Caldwell SH. Systematic review of risk factors for fibrosis progression in non-alcoholic steatohepatitis. J Hepatol. 2009;51:371-379.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Cited by in Crossref: 444]  [Cited by in RCA: 398]  [Article Influence: 23.4]  [Reference Citation Analysis (3)]
73.  Hagström H, Elfwén O, Hultcrantz R, Stål P. Steatohepatitis Is Not Associated with an Increased Risk for Fibrosis Progression in Nonalcoholic Fatty Liver Disease. Gastroenterol Res Pract. 2018;2018:1942648.  [RCA]  [PubMed]  [DOI]  [Full Text]  [Full Text (PDF)]  [Cited by in Crossref: 14]  [Cited by in RCA: 20]  [Article Influence: 2.5]  [Reference Citation Analysis (0)]
Footnotes

Peer review: Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Gastroenterology and hepatology

Country of origin: Algeria

Peer-review report’s classification

Scientific quality: Grade A, Grade D

Novelty: Grade B, Grade D

Creativity or innovation: Grade B, Grade B

Scientific significance: Grade B, Grade E

P-Reviewer: Kanda T, MD, PhD, Chief, Professor, Japan; Vargas-Beltran AM, MD, Mexico S-Editor: Hu XY L-Editor: Filipodia P-Editor: Wang CH

Write to the Help Desk